Abstract Abstract: This is an application for an administrative supplement to enhance the outcome of the parent grant: U01 AG046139 ?A Systems Approach to Targeting Innate Immunity in AD?. This Administrative Supplement aims to expand the cohort and enable validation studies within the competitive supplement originally funded under this parent award. In the original supplement we proposed to generate RNA sequence (RNAseq) from plasma in order to determine if transcriptomic signatures of AD can be detected in the periphery, and whether these peripheral transcriptomic signatures are correlated with brain transcriptomic signatures. We postulate that some of the transcriptional changes that are observed in AD brains can also be captured in blood or plasma of living subjects, as demonstrated by our prior preliminary data. We further hypothesized that some of the transcriptional changes that are congruent in brain and peripheral tissue will be observed prior to clinical manifestations of AD. If correct, then plasma transcriptome can be used as predictive biomarkers for AD. Further, they can be utilized to follow response to therapies that target the expression networks for these transcripts. Importantly, we are utilizing plasma for these studies, rather than more costly collections that are not readily available for most cohorts, such as PaxGene or peripheral blood mononuclear cells. We will analyze the transcriptome in the longitudinally-collected plasma samples from Mayo Clinic Study of Aging (MCSA) subjects who have multiple time-points of clinical, cognitive and neuroimaging outcomes. Since most clinical trials and prospective cohorts bank plasma longitudinally, our findings will have immediate applicability to the samples from those studies. Our specific aims are: 1) To generate and analyze additional plasma RNAseq data in order to identify peripheral transcriptomic signatures that are correlated with brain signatures: Plasma samples are already obtained from MCSA, where all subjects are clinically normal at baseline. The selected samples have either incident MCI/AD (?decliners?), or matched subjects who remain clinically normal (?non-decliners?) at follow-up. We are generating RNAseq data from two plasma samples per subject: one at baseline and the other after development of MCI/AD (?decliners?) or a matched time-point for ?non-decliners?. Both total RNA and microRNA are being quantified. With the requested supplemental funds we will: a) perform RNAseq on an additional 70 plasma samples which will bring the total to 187 plasma RNA samples; b) assess expression profiles for transcripts and networks for associations with available endophenotypes; c) compare the transcriptomic signatures from plasma and brain. 2) To validate differentially expressed transcripts and pathways utilizing a NanoString nCounter? Custom CodeSet for plasma transcript measurements: We aim to validate significant associations from Aim 1, for up to 130 plasma transcripts of interest. We expect to identify transcriptional networks and key transcripts that are altered in plasma prior to development of clinical AD and therefore will serve as predictive biomarkers.